Quantization using dither matrix noise based on noise use rate and accumulated error based on error use rate

ABSTRACT

A computer-readble medium stored with a program causing a computer to quantize a gray level causes the computer to perform a pixel selecting process; determining a noise use rate indicating the degree to which a dither matrix noise has an influence on the quantization and an error use rate indicating the degree to which an accumulated error has an influence on the quantization and determining the noise use rate and the error use rate corresponding to the corresponding pixel depending on the gray levels of the pixels sequentially selected in the pixel selecting process; and performing the quantization on the gray levels of the pixels sequentially selected in the pixel selecting process and performing the quantization using the dither matrix noise based on the noise use rate corresponding to the corresponding pixel and using the accumulated error based on the error use rate corresponding to the corresponding pixel.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a 371 of international application of PCTapplication serial no. PCT/JP2009/004934, filed on Sep. 28, 2009. Theentirety of the above-mentioned patent application is herebyincorporated by reference herein and made a part of this specification.

TECHNICAL FIELD

The present invention relates to a program, an image processingapparatus, and an image processing method.

BACKGROUND ART

In order to print an image with a printer, it is typically necessary toperform a quantization process on the image. The quantization process isa halftone process of converting an image expressed with a continuoustone into a gradation which can be expressed by the printer. Forexample, a dither process or an error diffusion process has been knownas a method of performing the quantization process.

A method of performing the quantization process selectively using thedither process and the error diffusion process has been known (forexample, see Japan Laid Open Publications JP-A-2006-240054 andJP-A-2008-87382). For example, in the method disclosed in Japan LaidOpen Publications JP-A-2006-240054, the dither process and the errordiffusion process are separately used depending on the gray levelranges. In the method disclosed in Japan Laid Open PublicationsJP-A-2008-87382, the dither process and the error diffusion process areseparately used depending on dot sizes by the use of a print head whichcan form N types of dots having different sizes.

DISCLOSURE OF INVENTION Problems to be Solved by the Invention

The dither process is a method of determining the presence of a halftonedot by applying the value (noise) of a dither matrix to pixel data, inwhich an original image is paneled with a dither matrix to perform thequantization process. Accordingly, there may be a problem of texturethat a specific pattern formed in the matrix is repeated. As a result,the image quality may degrade.

For example, to prevent the generation of texture specific to the ditherprocess, adjusting the value (noise) of the dither matrix to anappropriate value can be considered. However, the method suppressing thegeneration of texture by this adjustment requires a large amount ofoperation time and thus is not good in practice.

On the other hand, the error diffusion process is a method of preparinga threshold value to be compared with pixel data, comparing the value ofpixel data corrected by the use of a previously-calculated accumulatederror with the threshold value, and determining the presence of ahalftone dot depending on the comparison result. When the errordiffusion process is used, the error generated by the quantization canbe reduced over the entire image and thus the texture which is generatedby the dither process is not generated.

However, when the error diffusion process is used, problems such as adot delay where the arrangement of dots is delayed in the print resultof a highlighted part or shadowed part, a worm noise where dots areconnected, and a pattern noise where the dots in a halftone part arepartially arranged in a checkered pattern or randomly may be caused. Asa result, the image quality may degrade by image shift due to the dotdelay, generation of a streak pattern due to the worm noise, or thelike.

For example, when the dither process and the error diffusion process areseparately used as in Japan Laid Open Publication JP-A-2006-240054, aboundary line due to the difference between quantization methods may beformed in a part where the dither process is switched to the errordiffusion process, thereby degrading the image quality. When the methoddisclosed in Japan Laid Open Publication JP-A-2008-87382 is used, forexample, the error diffusion process is used in a highlighted part andthe dot delay is thus generated to cause the degradation of the imagequality.

Accordingly, there is a need for performing the quantization process bythe use of a more appropriate method. More specifically, there is a needfor a quantization process which can suppress, for example, the texture,the dot delay, the worm noise, and the pattern noise to realize ahigh-image-quality halftone process. Therefore, an object of theinvention is to provide a program, an image processing apparatus, and animage processing method which can solve the above-mentioned problems.

Means for Solving the Problems

As a result of eager study, the inventor of the present invention paidattention to the fact that the generability of texture varies dependingon the gray levels of pixels in the dither process. Attention is paid tothe fact that the generability of the dot delay or worm noise alsovaries depending on the gray levels of pixels in the error diffusionprocess. The inventor found that it is possible to appropriately performthe quantization process while suppressing the generation of texture,dot delay, and worm noise, for example, by distributing the influencesof the dither process and the error diffusion process without switchingthe dither process and the error diffusion process and performing anyone process. The invention has the following constitutions.

(Constitution 1) A program causing a computer to quantize a gray levelindicating the depth of color of each pixel in an image, thequantization including: a pixel selecting process of sequentiallyselecting pixels to be quantized; a use rate determining process ofdetermining a noise use rate indicating the degree to which a dithermatrix noise which is noise designated by a predetermined dither matrixhas an influence on the quantization and an error use rate indicatingthe degree to which an accumulated error obtained by accumulating aquantization error which is an error generated in the quantization onperipheral pixels has an influence on the quantization, in which thenoise use rate and the error use rate corresponding to the correspondingpixel are determined depending on the gray levels of the pixelssequentially selected through the pixel selecting process; and aquantization executing process of performing the quantization on thegray levels of the pixels sequentially selected through the pixelselecting process, in which the quantization is performed using thedither matrix noise based on the noise use rate corresponding to thecorresponding pixel and using the accumulated error based on the erroruse rate corresponding to the corresponding pixel.

The dither process and the error diffusion process are different fromeach other in the gray level range in which good image quality isobtained. Accordingly, when any one is used singly, the image qualitymay degrade due to the quantization in some gray level ranges. Forexample, when the dither process and the error diffusion process areswitched depending on the gray level range, a boundary line and the likemay be formed in a part in which both processes are switched.

On the contrary, by employing the above-mentioned constitution, forexample, the spatial frequency characteristic (hereinafter, referred toas the dither characteristic) of the dither process can have aninfluence on the spatial frequency characteristic (hereinafter, referredto as an error diffusion characteristic) of the error diffusion process.Accordingly, it is possible to perform the quantization, for example,through a combination of the dither characteristic into the errordiffusion characteristic. The spatial frequency characteristic is acharacteristic when the repeated ON and OFF pattern of dots in the printresult, which is one characteristic used to estimate the image quality,is grasped as a frequency.

According to this constitution, for example, unlike the case where thedither process and the error diffusion process are simply switched, itis possible to perform the quantization process more appropriately usingthe parts at which the processes are good. Accordingly, by employingthis constitution, it is possible to solve various problems in printcaused, for example, in the quantization process and to perform thequantization process through the use of a more appropriate method.

In the pixel selecting process, for example, lines of pixels aresequentially selected and then the pixels in the selected line aresequentially selected in a predetermined processing direction. In thiscase, the processing direction of the pixel selecting process may beswitched for each line to be processed. For example, it can beconsidered that the pixels are sequentially selected from left to rightin the odd lines and from right to left in the even lines. By employingthis constitution, for example, the quantization process is performed intwo directions and the diffusion direction of the error is not fixed,thereby more appropriately distributing the dots.

The use rate determining process determines the noise use rate and theerror use rate, for example, by the use of a predetermined computationalexpression. In this case, for example, by appropriately settingparameters of the expression, it is possible to appropriately suppressthe generation of a boundary line in a switching part between an area inwhich the dither characteristic is dominant and an area in which theerror diffusion characteristic is dominant. Accordingly, it is possibleto smoothly switch the methods of the quantization process. The optimalvalues of the parameters can be appropriately acquired, for example, byexperiments.

The program causes, for example, a computer to perform the processes foreach process color. In this case, for example, the dither matrix to beused may be changed for each process color. By employing thisconstitution, for example, the value of the dither matrix used in thequantization of the same pixel can be made to vary depending on theprocess colors. Accordingly, it is possible to appropriately prevent theovelapping of the dots.

It is preferable that, for example, noise of a blue noise characteristicbe used as the dither matrix noise. The blue noise characteristic is anoise biased to a high frequency, for example, when it is expressed bythe spatial frequency characteristic, and is hardly perceived with ahuman sense of sight. The blue noise characteristic is similar to thefrequency characteristic of the error diffusion process. Accordingly, byusing the dither matrix, it is easy to more easily switch the dithercharacteristic and the error diffusion characteristics.

The process may cause the computer to further perform, for example, aprocess of calculating an accumulated error. For example, the programmay cause the computer to further perform an error distribution processor the like. The error distribution process is a process of distributinga quantization error caused, for example, by the quantization of a pixeland serves to diffuse the quantization error into the peripheral pixelsof the corresponding pixel, for example, through the use of apredetermined diffusion filter (diffusion matrix). Accordingly, thevalue of the accumulated error corresponding to the respectiveperipheral pixels of the corresponding pixel is updated. For example, amatrix of Jarvis, Judice & Ninke can be suitably used as the diffusionfilter.

(Constitution 2) The program may cause the computer to additionallyperform on the pixels sequentially selected through the pixel selectingprocess: an error-corrected input value calculating process ofcalculating an error-corrected input value which is a gray level havingbeen corrected on the basis of the accumulated error, in which a valueobtained by adding the product of the error use rate and the accumulatederror corresponding to the corresponding pixel to the gray level of thecorresponding pixel is calculated as the error-corrected input value;and a noise-corrected threshold value calculating process of calculatinga noise-corrected threshold value which is a threshold value having beencorrected on the basis of the dither matrix noise as a threshold valueused for the quantization, in which a value obtained by adding theproduct of the noise use rate and the dither matrix noise correspondingto the corresponding pixel to a predetermined initial threshold value iscalculated as the noise-corrected threshold value, wherein thequantization executing process performs the quantization by comparingthe noise-corrected threshold value and the error-corrected input valuewith each other.

According to this constitution, it is possible to appropriately adjustthe degree to which the error diffusion characteristic has an influenceby adding the accumulated error multiplied by the error use rate to thegray level of the pixel as an input value of the quantization. By addingthe dither matrix noise multiplied by the noise use rate to the initialthreshold value, it is possible to appropriately adjust the degree towhich the dither characteristic has an influence.

Accordingly, by employing this constitution, it is possible toappropriately set the degrees to which the error diffusioncharacteristic and the dither characteristic have an influence, forexample, depending on the input value. Accordingly, it is possible toperform the quantization process more appropriately using the parts atwhich the processes are good depending on the input value.

(Constitution 3) The quantization executing process may include: amaximum value determining process of determining whether the gray levelof the pixel which is the input value of the quantization is equal tothe maximum value of an allowable gray level range; a minimum valuedetermining process of determining whether the gray level of the pixelwhich is the input value is equal to the minimum value of the allowablegray level range; and a quantization value acquiring process ofacquiring a quantization value as the result of the quantization,wherein when it is determined in the maximum value determining processthat the input value is equal to the maximum value, the quantizationvalue acquiring process acquires a value to be output when the graylevel is larger than the threshold value as the quantization value, andwherein when it is determined in the minimum value determining processthat the input value is equal to the minimum value, the quantizationvalue acquiring process acquires a value to be output when the graylevel is smaller than the threshold value as the quantization value.

For example, when the input value is equal to the maximum value, it isnecessary to set the quantization result to an output value (forexample, 1) to be output when the gray level is greater than thethreshold value, regardless of the error-corrected input value or thenoise-corrected threshold value. When the input value is equal to theminimum value, it is necessary to set the quantization result to anoutput value (for example, 0) to be output when the gray level issmaller than the threshold value, regardless of he error-corrected inputvalue or the noise-corrected threshold value.

On the contrary, by employing this constitution, it is possible toeasily and appropriately set the output value when the input value isequal to the maximum value or the minimum value. Accordingly, it ispossible to more appropriately perform the quantization process which iscarried out using both the accumulated error and the dither matrixnoise. The output values to be output when the gray level is greaterthan the threshold value and when the gray level is smaller than thethreshold value mean the output values indicating the comparison resultof the gray level with the threshold value, for example, when both theaccumulated error and the dither matrix noise are set to 0.

(Constitution 4) In determining the noise use rate and the error userate, the use rate determining process may set the noise use rate whenthe gray level of the pixel is a gray level corresponding to one of ahighlighted part and a shadowed part to a value larger than the noiseuse rate when the gray level of the pixel is a gray level correspondingto a halftone part of which the gray level is between the gray levels ofthe highlighted part and the shadowed part, and may set the error userate when the gray level of the pixel is a gray level corresponding toone of the highlighted part and the shadowed part to a value smallerthan the error use rate when the gray level of the pixel is the graylevel corresponding to the halftone part.

The noise use rate is, for example, 1 (100%) in the highlighted part andthe shadowed part and varies to gradually decrease as it goes closer tothe halftone. The error use rate is, for example, 0 (0%) at both ends ofthe gray level range and varies to be the value 1 (100%) just before thegray level range of a texture-generated part.

According to this constitution, for example, when the influence of theerror diffusion characteristic is great, the noise use rate is set to behigh and the error use rate is set to be low in the highlighted part andthe shadowed part in which the dot delay can be easily generated.Accordingly, since the influence of the dither characteristic ofdistributing and arranging the dots becomes greater, for example, in thehighlighted part and the shadowed part, it is possible to appropriatelysuppress the generation of the dot delay.

By performing the quantization process in the halftone part with thegreater influence of the error diffusion characteristic, for example, itis possible to obtain a more natural pseudo-gradation. For example, bylowering the noise use rate and raising the error use rate in the graylevel range of the texture-generated part to give a change to thearrangement of dots, for example, it is possible to appropriatelysuppress the generation of texture.

(Constitution 5) The use rate determining process may set the noise userate to a value equal to or larger than the lowest noise use rate set toa value larger than 0 in advance even when the gray level of the pixelhas any value.

When the noise use rate in the halftone part is set to 0 (0%) and theerror use rate therein is set to 1 (100%), a pattern noise specific tothe error diffusion characteristics maybe generated. The reason forgenerating the pattern noise in the halftone part is that thearrangement of dots can have a checkered pattern, for example, since theerror diffusion characteristic in the halftone part exhibits a very highfrequency and the checkered pattern is partially generated since the dotarrangement pattern is not fixed like the dither process. On thecontrary, by providing the lowest noise use rate so as not to set thenoise use rate to 0, the influence of the dither characteristic is madeto slightly decrease and the influence of the error diffusioncharacteristic is made to increase, for example, in the halftone part.Accordingly, since the influence of the dither process on the dotarrangement pattern decreases, the whole arrangement pattern can beeasily fixed and the partial checkered pattern is hardly generated. As aresult, for example, it is possible to appropriately suppress thepattern noise.

(Constitution 6) The use rate determining process may use a firsthighlight reference value set in advance and a second highlightreference value larger than the first highlight reference value as areference indicating the gray level range of the highlighted part; mayuse a first shadow reference value set in advance and a second shadowreference value larger than the first shadow reference value as areference indicating the gray level range of the shadowed part; may usea first halftone reference value which is larger than the secondhighlight reference value and smaller than the first shadow referencevalue and a second halftone reference value which is larger than thefirst halftone reference value and smaller than the first shadowreference value as a reference indicating the gray level range at thecenter of the halftone part; may set the noise use rate to 1 when thegray level of the pixel is equal to or less than the first highlightreference value or when the gray level of the pixel is equal to or morethan the second shadow reference value; may set the noise use rate tothe lowest noise use rate when the gray level of the pixel is equal toor more than the first halftone reference value and equal to or lessthan the second halftone reference value; may set the noise use rate toa value which is equal to or more than the lowest noise use rate andequal to or less than 1 and which gradually decreases from 1 dependingon the difference between the gray level of the pixel and the firsthighlight reference value when the gray level of the pixel is equal toor more than the first highlight reference value and equal to or lessthan the first halftone reference value; may set the noise use rate to avalue which is equal to or more than the lowest noise use rate and equalto or less than 1 and which gradually increases from the lowest noiseuse rate depending on the difference between the gray level of the pixeland the second halftone reference value when the gray level of the pixelis equal to or more than the second halftone reference value and equalto or less than the second shadow reference value; may set the error userate to 1 when the gray level of the pixel is equal to or more than thesecond highlight reference value and equal to or less than the firstshadow reference value; may set the error use rate to a value which isequal to or more than 0 and equal to or less than 1 and which graduallydecreases from 1 depending on the difference between the secondhighlight reference value and the gray level when the gray level of thepixel is equal to or less than the second highlight reference value; andmay set the error use rate to a value which is equal to or more than 0and equal to or less than 1 and which gradually decreases from 1depending on the difference between the gray level of the pixel and thefirst shadow reference value when the gray level of the pixel is equalto or more than the first shadow reference value.

By employing this configuration, it is possible to appropriately set theerror use rate and the noise use rate, for example, depending on thegray level of a pixel. Accordingly, it is possible to appropriatelyperform the quantization process more appropriately using the parts atwhich the error diffusion process and the dither process are good.

(Constitution 7) The use rate determining process may additionally use athird highlight reference value which is larger than 0 and equal to orless than the first highlight reference value as the referenceindicating the gray level range of the highlighted part; mayadditionally use a third shadow reference value which is equal to ormore than the second shadow reference value and smaller than the maximumvalue of the allowable gray level range as the reference indicating thegray level range of the shadowed part; may set the error use rate to 0when the gray level of the pixel is equal to or less than the thirdhighlight reference value; may set the error use rate to a valueobtained by dividing the difference between the gray level of the pixeland the third highlight reference value by the difference between thesecond highlight reference value and the third highlight reference valuewhen the gray level of the pixel is equal to or more than the thirdhighlight reference value and equal to or less than the second highlightreference value; may set the error use rate to a value obtained bydividing the difference between the third shadow reference value and thegray level of the pixel by the difference between the third shadowreference value and the first shadow reference value when the gray levelof the pixel is equal to or more than the first shadow reference valueand equal to or less than the third shadow reference value; and may setthe error use rate to 0 when the gray level of the pixel is equal to ormore than the third shadow reference value. By employing thisconstitution, for example, it is possible to more appropriately set theerror use rate.

(Constitution 8) There is provided an image processing apparatusquantizing a gray level indicating the depth of color of each pixel inan image, including: a pixel selecting unit that sequentially selectspixels to be quantized; a use rate determining unit that determines anoise use rate indicating the degree to which a dither matrix noisewhich is a noise designated by a predetermined dither matrix has aninfluence on the quantization and an error use rate indicating thedegree to which an accumulated error obtained by accumulating aquantization error which is an error generated in the quantization onperipheral pixels has an influence on the quantization and thatdetermines the noise use rate and the error use rate corresponding tothe corresponding pixel depending on the gray levels of the pixelssequentially selected by the pixel selecting unit; and a quantizationexecuting unit that performs the quantization on the gray levels of thepixels sequentially selected by the pixel selecting unit and thatperforms the quantization using the dither matrix noise based on thenoise use rate corresponding to the corresponding pixel and using theaccumulated error based on the error use rate corresponding to thecorresponding pixel. By employing this constitution, for example, it ispossible to achieve the same advantages as in Constitution 1.

The image processing apparatus may be, for example, a computer operatingin accordance with a predetermined program. In this case, for example, aCPU of the computer serves as the constituents of the image processingapparatus in accordance with the program.

(Constitution 9) There is provided an image processing method ofquantizing a gray level indicating the depth of color of each pixel inan image, including: a pixel selecting step of sequentially selectingpixels to be quantized; a use rate determining step of determining anoise use rate indicating the degree to which a dither matrix noisewhich is noise designated by a predetermined dither matrix has aninfluence on the quantization and an error use rate indicating thedegree to which an accumulated error obtained by accumulating aquantization error which is an error generated in the quantization onperipheral pixels has an influence on the quantization and determiningthe noise use rate and the error use rate corresponding to thecorresponding pixel depending on the gray levels of the pixelssequentially selected in the pixel selecting step; and a quantizationexecuting step of performing the quantization on the gray levels of thepixels sequentially selected in the pixel selecting step and performingthe quantization using the dither matrix noise based on the noise userate corresponding to the corresponding pixel and using the accumulatederror based on the error use rate corresponding to the correspondingpixel. Accordingly, for example, it is possible to achieve the sameadvantages as in Constitution 1.

Advantage of the Invention

According to the invention, it is possible to perform the quantizationprocess, for example, through the use of a more appropriate method.Accordingly, it is possible to appropriately suppress the generation oftexture, the dot delay, the generation of a pattern noise, and the like,for example, in the halftone process.

BRIEF DESCRIPTION OF DRAWINGS

FIGS. 1( a)˜1(b) are diagrams illustrating a program according to anembodiment of the invention, where FIG. 1( a) shows an example of theconfiguration of a printing system 10 using the program and FIG. 1( b)schematically shows a quantization process performed by an imageprocessing apparatus 12.

FIG. 2 is a flowchart illustrating an example of the quantizationoperation.

FIGS. 3( a)˜3(b) are diagrams specifically illustrating a pixelselecting process S102, where FIG. 3( a) shows an example of a procedureof sequentially selecting pixels and FIG. 3( b) shows an example of theadvantage of a bidirectional process.

FIG. 4 is a diagram illustrating exemplary graph and computationalexpression correlating an error use rate Re, a noise use rate Rn, and agray level In(x, y) with each other.

FIG. 5 is a flowchart illustrating an example of a process ofcalculating the error use rate Re.

FIG. 6 is a flowchart illustrating an example of a process ofcalculating a noise use rate Rn.

FIG. 7 is a flowchart illustrating an example of the operation of aquantization executing process S110.

FIGS. 8( a)˜8(b) are diagrams illustrating an example of a diffusionfilter used in this embodiment, where FIG. 8( a) shows an example ofdiffusion filters used in the respective directions of the bidirectionalprocess and FIG. 8( b) shows an example of an error distributing method.

FIG. 9 is a flowchart illustrating an example of the operation of anerror distributing process S112.

FIGS. 10( a)˜10(d) are diagrams illustrating an example of a printingresult according to the embodiment along with a printing resultaccording to a reference example, where FIG. 10( a) shows an example ofthe printing result when only a known typical error diffusion process isperformed, FIG. 10( b) shows an example of the printing result when onlya known dither process is performed, FIG. 10( c) shows an example of theprinting result when the dither process and the error diffusion processare simply switched depending on the gray level range, and FIG. 10( d)shows an example of the printing result according to the embodiment.

BEST MODE FOR CARRYING OUT THE INVENTION

Hereinafter, an embodiment of the invention will be described withreference to the accompanying drawings. FIGS. 1( a)˜1(b) are diagramsillustrating a program according to an embodiment of the invention. FIG.1( a) shows an example of the configuration of a printing system 10using the program. In this embodiment, the printing system 10 includesan image processing apparatus 12 and a printing machine 14.

The image processing apparatus 12 is an apparatus performing an imageforming process such as a RIP (Raster Image Processor) process. Theimage processing apparatus 12 generates printable data indicating animage in the format which can be analyzed by the printing machine 14 bydeveloping an original image indicated by print data.

In this embodiment, the image processing apparatus 12 quantizes at leastthe gray level indicating the depth of color of each pixel in theoriginal image in the image forming process. In this case, the imageprocessing apparatus 12 performs the quantization for each process colorused in the printing machine 14. Accordingly, the image processingapparatus 12 forms a halftone image corresponding to each process coloron the basis of the print data.

The image processing apparatus 12 is, for example, a host PC controllingthe printing machine 14 and operates as an image processing apparatus inaccordance with a predetermined program. The image processing apparatus12 may receive the print data from, for example, another PC. The printdata may be prepared by the image processing apparatus 12 by a user.

The printing machine 14 is, for example, an ink jet printer and printsan image on the basis of printable data received from the imageprocessing apparatus 12. In this embodiment, the printing machine 14performs a color printing operation using the colors of CMYK ink asprocess colors. The printing machine 14 may perform the printingoperation using additional colors of ink.

FIG. 1( b) is a diagram schematically illustrating the quantizationprocess performed by the image processing apparatus 12. The imageprocessing apparatus 12 forms a pseudo-halftone image which is halftoneimage by quantizing the original image for each process color. Thequantization is a process of converting the gray levels In(x, y) at thecoordinates of the original image into quantization values out (x, y) atthe same coordinates of the pseudo-halftone image.

In this embodiment, the image processing apparatus 12 performs thequantization through the use of a method (hybrid error diffusionprocess) using both a dither matrix noise D(i, j) and an accumulatederror E(x, y). The image processing apparatus 12 additionally uses anoise use rate Rn and an error use rate Re set to values in the range of0 to 1 (0% to 100%) as parameters based on the dither matrix noise D(i,j) and the accumulated error E(x, y).

The noise use rate Rn is a parameter indicating the degree to which thedither matrix noise D(i, j) has an influence on the quantization processand is calculated on the basis of the gray level In(x, y) of the pixelto be quantized. The image processing apparatus 12 performs thequantization using the product of the dither matrix noise D(i, j) andthe noise use rate Rn without using the dither matrix noise D(i, j)itself. Accordingly, the image processing apparatus 12 uses the dithermatrix noise D(i, j) depending on the noise use rate Rn corresponding toeach pixel.

The error use rate Re is a parameter indicating the degree to which theaccumulated error E(x, y) has an influence on the quantization processand is calculated on the basis of the gray level In(x, y) of the pixelto be quantized. The image processing apparatus 12 calculates anerror-corrected input value In′(x, y) corresponding to the gray levelsIn(x, y) of each pixel using the product of the accumulated error E(x,y) and the error use rate Re without using the accumulated error E(x, y)itself. The image processing apparatus performs the quantization processusing the calculated error-corrected input value In′(x, y). Accordingly,the image processing apparatus 12 uses the accumulated error E(x, y)depending on the error use rate Re corresponding to each pixel. Thequantization process will be described in more detail later.

According to this embodiment, for example, it is possible to have aninfluence of the spatial frequency characteristic (dithercharacteristic) of the dither process on the spatial frequencycharacteristic (error diffusion characteristic) of the error diffusionprocess. Accordingly, the quantization can be performed, for example,through the use of a method in which the dither characteristic iscombined into the error diffusion characteristic. In this case, forexample, unlike the case where the dither process and the errordiffusion process are simply switched, it is possible to appropriatelyprevent the generation of a boundary line due to the switching of theprocesses.

Accordingly, according to this embodiment, it is possible, for example,to perform the quantization process using appropriately using the partsat which the processes are good. As a result, for example, it ispossible to appropriately solve various problems in print caused in thequantization process and to perform the quantization process through theuse of a more appropriate method.

The dither matrix noise D(i, j) is, for example, a value designated by apredetermined dither matrix. The dither matrix noise D(i, j) may beidentical or similar to the dither matrix noise used in the ditherprocess according to the background art. It is preferable that, forexample, noise of a blue noise characteristic is used as the dithermatrix noise D(i, j). It is preferable that the image processingapparatus 12 changes the dither matrix to be used for each processcolor.

The accumulated error E(x, y) is a value obtained by accumulating thequantization errors Q(x, y) which are errors based on the quantizationon peripheral pixels and is calculated using a predetermined diffusionfilter (diffusion matrix). The calculated accumulated error E(x, y) isstored, for example, in an error buffer. The image processing apparatus12 calculates the accumulated error E(x, y) through the use of themethod identical or similar to calculating the accumulated error used inthe error diffusion process according to the background art.

FIG. 2 is a flowchart illustrating an example of the quantizationoperation. The image processing apparatus 12 performs the followingprocess, for example, for each process color.

In the quantization operation, the image processing apparatus 12according to this embodiment first selects a pixel to be quantized fromthe original image (pixel selecting process S102). Then, the imageprocessing apparatus calculates the noise use rate Rn and the error userate Re corresponding to the selected pixel depending on the gray levelIn(x, y) of the corresponding pixel. Accordingly, the image processingapparatus 12 determines the noise use rate Rn and the error use rate Reused in quantizing the pixel (use rate determining process S104).

Subsequently, the image processing apparatus 12 calculates theerror-corrected input value In′(x, y) which is the gray level afterperforming the correction using the accumulated error E(x, y)(error-corrected input value calculating process S106). In this process,for example, the image processing apparatus 12 adds the product of theerror use rate Re corresponding to the pixel selected in the pixelselecting process S102 and the accumulated error E(x, y) to the graylevel In(x, y) of the corresponding pixel and calculates the added valueas the error-corrected input value In′(x, y).

The image processing apparatus 12 calculates a noise-corrected thresholdvalue Th′ which is a threshold value reflecting the dither matrix noiseD(i, j) as the threshold value used in the quantization (noise-correctedthreshold value calculating process S108). In this process, for example,the image processing apparatus 12 adds the product of the noise use rateRn corresponding to the pixel selected in the pixel selecting processS102 and the dither matrix noise D(i, j) to a predetermined initialthreshold value Th and calculates the added value as the noise-correctedthreshold value Th′.

The image processing apparatus 12 compares the error-corrected inputvalue In′(x, y) with the calculated noise-corrected threshold value Th′.Accordingly, the image processing apparatus 12 executes the quantizationon the pixel selected in the pixel selecting process S102 (quantizationexecuting process S110).

Subsequently, the image processing apparatus 12 diffuses thequantization error Q(x, y) generated through the quantization of thepixel to the peripheral pixels through the use of a diffusion filter(error distributing process S112). Accordingly, the image processingapparatus 12 adds the quantization error Q(x, y) to the value of thediffusion filter corresponding to the distribution destinationcoordinates of the peripheral pixels and updates the value of theaccumulated error E(x, y) corresponding to the respective peripheralpixels.

After the error distributing process S112, the image processingapparatus 12 determines whether the pixel having been subjected to thequantization is the final pixel of the original image (final pixeldetermining process S114). When it is determined that the pixel is thefinal pixel (Yes in S114), the image processing apparatus ends thequantization process to the original image. When it is determined thatthe pixel is not the final pixel (No in S114), the image processingapparatus selects a next pixel in the pixel selecting process S102again. Accordingly, the image processing apparatus 12 sequentiallyselects the pixels to be quantized in the pixel selecting process S102.By performing the processes subsequent to the pixel selecting processS102 on the pixels to be sequentially selected, the image processingapparatus performs the quantization on the pixels.

According to this embodiment, for example, by adding the accumulatederror E(x, y) multiplied by the error use rate Re to the gray levelIn(x, y), it is possible to appropriately adjust the degree to which theerror diffusion characteristic has an influence. By adding the dithermatrix noise D(i, j) multiplied by the noise use rate Rn to the initialthreshold value Th, it is possible to appropriately adjust the degree towhich the dither characteristic has an influence.

Accordingly, it is possible to appropriately set the degree to which theerror diffusion characteristic and the dither characteristic have aninfluence, for example, depending on the gray level In(x, y) as theinput value. It is also possible to perform the quantization processappropriately using the parts at which the error diffusion process andthe dither process are good. Hereinafter, the processes of thequantization operation will be described in more detail.

FIGS. 3( a)˜3(b) are diagrams illustrating the pixel selecting processS102 in more detail. FIG. 3( a) shows an example of the sequence ofsequentially selecting the pixels. In the pixel selecting process S102of this embodiment, the image processing apparatus 12 sequentiallyselects, for example, lines of pixels and then sequentially selects thepixels in the selected line in a predetermined processing direction. Theimage processing apparatus 12 switches the processing direction for eachline to be processed. For example, the image processing apparatus 12sequentially selects the pixels from left to right in the odd lines andfrom right to left in the even lines. Accordingly, the image processingapparatus 12 performs the quantization process in two directions.

FIG. 3( b) is a diagram illustrating an example of an advantage of thebidirectional process and shows examples of the quantization result whenthe only one direction is used as the processing direction and when twodirections are used as the processing direction. When the bidirectionalprocess is performed, the diffusing direction of the error is not fixedand it is thus possible to more appropriately distribute the dots. As aresult, compared with the case where the quantization process isperformed in only one direction, it is possible to more appropriatelyprevent the generation of the worm noise or the like.

FIGS. 4 to 6 are diagrams illustrating the use rate determining processS104 in more detail. FIG. 4 shows examples of a graph and acomputational expression correlating the error use rate Re, the noiseuse rate Rn, and the gray level In(x, y) (hereinafter, referred to as aninput value).

In this embodiment, the image processing apparatus 12 calculates theerror use rate Re and the noise use rate Rn on the basis of a functioncontinuously varying with respect to the input value In in the range of0 as the minimum input value MinIn to the maximum input value MaxIn. Themaximum input value MaxIn and the minimum input value MinIn are, forexample, the maximum value and the minimum value in the allowable rangeof the gray level as the input value In, respectively.

In this function, the image processing apparatus 12 uses ahighlight-side error use rate minimum gray level Hes which is an exampleof the third highlight reference value, a highlight-side noise use ratemaximum gray level Hn which is an example of the first highlightreference value, and a highlight-side error use rate maximum gray levelHe which is an example of the second highlight reference value as areference indicating the gray level range in the highlighted part. Theimage processing apparatus uses a shadow-side error use rate maximumgray level Se which is an example of the first shadow reference value, ashadow-side noise use rate maximum gray level Sn which is an example ofthe second shadow reference value, and a shadow-side error use rateminimum gray level Ses which is an example of the third shadow referencevalue as a reference indicating the gray level range in the shadowedpart. The image processing apparatus uses a highlight-side noise userate 0% gray level Hnz, a shadow-side noise use rate 0% gray level Snz,a first halftone reference value C1, and a second halftone referencevalue C2 as a reference indicating the gray level range including theinitial threshold value Th at the center of the halftone part.

These parameters are set to satisfy at least Hes≦Hn<He<Se<Sn≦Ses andHn<Hnz<Snz<Sn. In this embodiment, the parameters are set to satisfy themagnitude relationship 0(MinIn)<Hes≦Hn<He<C1<Hnz<Th<Snz<C2<Se<Sn≦Ses<MaxIn.

In the use rate determining process S104, the image processing apparatus12 determines the error use rate Re and the noise use rate Rn on thebasis of the computational expression shown below the graph. Here, whenthe noise use rate Rn calculated by the use of this expression issmaller than a predetermined lowest noise use rate RnMin, the imageprocessing apparatus 12 sets the noise use rate Rn to the lowest noiseuse rate RnMin. Accordingly, the image processing apparatus 12 sets thenoise use rate Rn to a value equal to or more than the lowest noise userate RnMin even when the gray level of a pixel has any value.

The error use rate Re and the noise use rate Rn are set to the values inthe range of 0% to 100% (the values in the range of 0 to 1). When avalue of 100% or more is calculated through the use of the computationalexpression shown below the graph, the value is set to 100%. When thecalculated value is equal or less than 0%, the value is set to 0%.

The lowest noise use rate RnMin is set to a value greater than 0 inadvance, for example, when setting or adjusting the parameters. It canbe considered, for example, that the lowest noise use rate RnMin is setto a value equal to or more than 0.1 (10%). For example, it ispreferable that the lowest noise use rate RnMin is set to be, forexample, in the range of 0.1 to 0.2 (10% to 20%). As can be seen fromthe graph, when the input value In is identical to the first halftonereference value C1 or the second halftone reference value C2, the noiseuse rate Rn calculated through the use of the computational expressionis identical to the lowest noise use rate RnMin.

For example, when the input value In is equal to or more than thehighlight-side error use rate maximum gray level He and equal to or lessthan the shadow-side error use rate maximum gray level Se through theuse of this method, the image processing apparatus 12 sets the error userate Re to 1 (100%). For example, when the input value In is equal to orless than the highlight-side error use rate minimum gray level Hes, theimage processing apparatus sets the error use rate Re to 0. When theinput value In is equal to or more than the highlight-side error userate minimum gray level Hes and equal to or less than the highlight-sideerror use rate maximum gray level He, the image processing apparatussets the error use rate Re to a value calculated by (In−Hes)/(He−Hes).Accordingly, for example, when the input value In is equal to or lessthan the highlight-side error use rate maximum gray level He, the imageprocessing apparatus sets the error use rate Re to a value which is inthe range of 0 to 1 (100%) and which gradually decreases from 1depending on the difference between the highlight-side error use ratemaximum gray level He and the input value In.

For example, when the input value In is equal to or more than theshadow-side error use rate maximum gray level Se and equal to or lessthan the shadow-side error use rate minimum gray level Ses, the erroruse rate Re is set to a value calculated by (Ses−In)/(Ses−Se). When theinput value In is equal to or more than the shadow-side error use rateminimum gray level Ses, the error use rate Re is set to 0. Accordingly,for example, when the input value In is equal to or more than theshadow-side error use rate maximum gray level Se, the error use rate Reis set to a value which is in the range of 0 to 1 (100%) and whichgradually decreases from 1 depending on the difference between the inputvalue In and the shadow-side error use rate maximum gray level Se.

In this case, the error use rate Re from the highlighted part to thehalftone part slowly increase, for example, from the highlight-sideerror use rate minimum gray level Hes with respect to the input value Inand becomes the maximum value at the highlight-side error use ratemaximum gray level He. The error use rate Re from the shadowed part tothe halftone part slowly decreases from the shadow-side error use ratemaximum gray level Se with respect to the input value In and becomes theminimum value at the shadow-side error use rate minimum gray level Ses.

Accordingly, the image processing apparatus 12 sets, for example, theerror use rate Re when the input value In is a gray level correspondingto any of the highlighted part and the shadowed part to a value smallerthan the error use rate Re when the input value is a gray levelcorresponding to the halftone part. In this case, the error use rate Rehas the value of 0 (0%), for example, at both ends of the gray levelrange and varies so as to have a value 1 (100%) just before thetexture-generated parts Hd and Sd which is a gray level range where thetexture specific to the dither process is generated. By employing thisconstitution, for example, it is possible to appropriately achieve theconstitution in which the error use rate Re is mainly used for thehalftone part.

For example, when the input value In is equal to or less than thehighlight-side noise use rate maximum gray level Hn or when the inputvalue is equal to or more than the shadow-side noise use rate maximumgray level Sn, the image processing apparatus 12 sets the noise use rateRn to 1 (100%). When the input value In is equal to or more than thefirst halftone reference value C1 and equal to or less than the secondhalftone reference value C2, the image processing apparatus sets thenoise use rate Rn to the lowest noise use rate RnMin.

For example, when the input value In is equal to or more than thehighlight-side noise use rate maximum gray level Hn and equal to or lessthan the first halftone reference value C1, the image processingapparatus 12 sets the noise use rate Rn to a value which is equal to ormore than the lowest noise use rate RnMin and equal or less than 1(100%) and which gradually decreases from 1 depending on the differencebetween the input value In and the highlight-side noise use rate maximumgray level Hn. For example, when the input value In is equal to or morethan the second halftone reference value C2 and equal to or less thanthe shadow-side noise use rate maximum gray level Sn, the imageprocessing apparatus 12 sets the noise use rate Rn to a value which isequal to or more than the lowest noise use rate RnMin and equal to orless than 1 (100%) and which gradually increases from the lowest noiseuse rate RnMin depending on the difference between the input value Inand the second halftone reference value C2.

Accordingly, the image processing apparatus 12 sets, for example, thenoise use rate Rn when the input value In is a gray level correspondingto any of the highlighted part and the shadowed part to a value greaterthan the noise use rate Rn when the input value is a gray levelcorresponding to the halftone part. In this case, the noise use rate Rnhas a value of 1 (100%), for example, in the highlighted part and theshadowed part and varies so as to slowly decrease as it goes closer tothe halftone part.

According to this embodiment, for example, when the influence of theerror diffusion characteristic becomes greater, the noise use rate Rn inthe highlighted part and the shadowed part in which the dot delay can beeasily generated is set to be higher and the error use rate Re is set tobe lower. Accordingly, since the influence of the dither characteristicallowing the dots to be distributed and arranged becomes greater, forexample, in the highlighted part and the shadowed part, it is possibleto appropriately suppress the generation of the dot delay.

By performing the quantization process on the halftone part with theincreased influence of the error diffusion characteristic, for example,it is possible to obtain a more natural pseudo-gradation. For example,by lowering the noise use rate Rn and raising the error use rate Re inthe gray level range of the texture-generated part, it is possible tovary the arrangement of dots. As a result, for example, it is possibleto appropriately suppress the generation of texture.

For example, by providing the lowest noise use rate RnMin so as not toset the noise use rate Rn to 0, for example, it is possible to enhancethe influence of the error diffusion characteristic while giving aslight influence of the dither characteristic to the halftone part. As aresult, for example, it is possible to appropriately suppress thepattern noise.

For example, by slowly varying the magnitude of the influence of thedither characteristic and the magnitude of the influence of the errordiffusion characteristic depending on the computational expressions forcalculating the error use rate Re and the noise use rate Rn, it ispossible to appropriately suppress the generation of a boundary line inthe switching part between an area in which the dither characteristic isdominant and an area in which the error diffusion characteristic isdominant. As a result it is possible to smoothly switch the methods ofthe quantization process.

Therefore, according to this embodiment, it is possible to appropriatelyset the error use rate Re and the noise use rate Rn, for example,depending on the gray level of a pixel. Accordingly, it is possible toappropriately perform the quantization process more appropriately usingthe parts at which the error diffusion process and the dither processare good.

The process of calculating the error use rate Re and the noise use rateRn will be described in more detail below. FIG. 5 is a flowchartillustrating an example of the process of calculating the error use rateRe.

In calculating the error use rate Re, the image processing apparatus 12first determines whether the input value In is in the range of equal toor more than the highlight-side error use rate maximum gray level He andequal to or less than the shadow-side error use rate maximum gray levelSe (S202). When it is determined that the input value is in the range(Yes in S202), the image processing apparatus sets the error use rate Reto 1 (100%) which is the maximum use rate (S204).

When it is determined that the input value is not in the range (No inS202), the image processing apparatus additionally determines whetherthe input value In is in the range of more than the highlight-side erroruse rate minimum gray level Hes and less than the highlight-side erroruse rate maximum gray level He (S206). When it is determined that theinput value is in the range (Yes in S206), the image processingapparatus sets the error use rate Re to a value calculated byRe=(In−Hes)/(He−Hes) (S208).

When it is determined in S206 that the input value In is not in therange (No in S206), the image processing apparatus 12 additionallydetermines whether the input value In is in the range of more than theshadow-side error use rate maximum gray level Se and less than theshadow-side error use rate minimum gray level Ses (S210). When it isdetermined that the input value is in the range (Yes in S210), the imageprocessing apparatus sets the error use rate Re to a value calculated byRe=(Ses−In)/(Ses−Se) (S212). When it is determined in S210 that theinput value In is not in the range (No in S210), the image processingapparatus 12 sets the error use rate Re to 0 (0%) (S214).

The image processing apparatus 12 employs the error use rate Re set inany of S204, S208, S212, and S214 as the error use rate Re correspondingto the input value In (S216). According to this embodiment, it ispossible to appropriately calculate the error use rate Re.

FIG. 6 is a flowchart illustrating an example of the process ofcalculating the noise use rate Rn. In calculating the noise use rate Rn,the image processing apparatus 12 first determines whether the inputvalue In is in the range of more than the highlight-side noise use ratemaximum gray level Hn and less than the highlight-side noise use rate 0%gray level Hnz (S302). When it is determined that the input value is inthe range (Yes in S302), the image processing apparatus sets the noiseuse rate Rn to a value calculated by Rn=(Hnz−In)/(Hnz−Hn) (S304).

When it is determined that the input value is not in the range (No inS302), the image processing apparatus additionally determines whetherthe input value In is in the range of more than the shadow-side noiseuse rate 0% gray level Snz and less than the shadow-side noise use ratemaximum gray level Sn (S306). When it is determined that the input valueis in the range (Yes in S306), the image processing apparatus sets thenoise use rate Rn to a value calculated by Rn=(In−Snz)/(Sn−Snz) (S308).

After setting the noise use rate Rn to the calculated value in S304 orS308, the image processing apparatus determines whether the set noiseuse rate Rn is greater than the lowest noise use rate RnMin which is theminimum use rate (S310). When it is determined that the noise use rateRn is equal to or less than the lowest noise use rate RnMin (No inS310), the image processing apparatus changes the value of the noise userate Rn to the lowest noise use rate RnMin (S312) and performs theprocess of S316. When it is determined that the noise use rate Rn isgreater than the lowest noise use rate RnMin (Yes in S310), the imageprocessing apparatus performs the process of S316 without changing thevalue of the noise use rate Rn.

When it is determined in S306 that the input value In is not in therange (No in S306), the image processing apparatus 12 sets the noise userate Rn to 1 (100%) which is the maximum use rate (S314). Then, theimage processing apparatus 12 employs the noise use rate Rn set in anyof S304, S308, S312, and S314 as the noise use rate Rn corresponding tothe input value In (S316). According to this embodiment, it is possibleto appropriately calculate the noise use rate Rn.

FIG. 7 is a flowchart illustrating an example of the operation of thequantization executing process S110. In the quantization executingprocess S110 of this example, the image processing apparatus 12 firstdetermines whether the input value In is identical to the maximum inputvalue MaxIn (maximum value determining process S402). When it isdetermined that the input value is identical to the maximum input value(Yes in S402), the image processing apparatus sets the output valueindicating the quantization result to 1 (S404). The value 1 is anexample of a value to be output when the input value In is more than thethreshold value Th. The error value used in the error distributingprocess S112 later is set to the difference In′-MaxIn between theerror-corrected input value In′ and the maximum input value MaxIn alongwith the setting of the output value.

When it is determined in S402 that the input value In is not identicalto the maximum input value MaxIn (No in S402), the image processingapparatus 12 additionally determines whether the input value In isidentical to the minimum input value MinIn (minimum value determiningprocess S406). When it is determined that the input value is identicalto the minimum input value (Yes in S406), the image processing apparatussets the output value to 0 (S408). The value 0 is an example of thevalue to be output when the input value In is less than the thresholdvalue Th. The image processing apparatus sets the error value to theerror-corrected input value In′ along with the setting of the outputvalue.

When it is determined in S406 that the input value In is not identicalto the minimum input value MinIn (No in S406), the image processingapparatus 12 determines whether the error-corrected input value In/′ ismore than the noise-corrected threshold value Th′ (S410). When it isdetermined that the error-corrected input value is more than thenoise-corrected threshold value (Yes in S410), the image processingapparatus sets the output value to 1 and sets the error value toIn′−MaxIn (S412). When it is determined in S410 that the error-correctedinput value In′ is equal to or less than the noise-corrected thresholdvalue Th′ (No in S410), the image processing apparatus sets the outputvalue to 0 and sets the error value to In′ (S414).

The image processing apparatus 12 acquires the output value and theerror value set in S404, S408, S412, or S414 as the quantization valueand the error value serving as the result of the quantization executingprocess S110 (quantization value acquiring process S416). The acquirederror value is given and taken to and from the later error distributingprocess S112. According to this embodiment, for example, it is possibleto easily and appropriately set the output value and the error value.

FIGS. 8( a), 8(b) and 9 are diagrams illustrating the error distributingprocess S112 in more detail. FIGS. 8( a) and 8(b) show examples of thediffusion filter used in this example. FIG. 8( a) shows examples of thediffusion filters used in the directions of the bidirectional process.

In this example, the diffusion filter is, for example, a matrix ofJarvis, Judice & Ninke. The filters shown in the drawing are used in amain scanning direction and a reverse main scanning direction which arethe directions of the bidirectional process. In the filters shown in thedrawing, the position to which sign * is written represents thecoordinate [0, 0] (origin) of the input value In. The numerical valuesin the matrixes represent distribution ratios at which the error isdistributed to the peripheral pixels.

FIG. 8( b) shows an example of the error distributing method. In theprocess of distributing the error to the peripheral pixels, when thecoordinate of an error distribution destination departs from an imagewidth, the image processing apparatus 12 changes the coordinate of thedistribution destination to the head coordinate of the next line. Whenthe opposite coordinate departs from the range, the same process isperformed. When the line of the distribution destination is not present,the image processing apparatus 12 does not distribute the error. Whenthe coordinate of the distribution destination indicates a processedpixel, the image processing apparatus does not distribute the error.

FIG. 9 is a flowchart illustrating an example of the operation of theerror distributing process S112. In the error distributing process S112,the image processing apparatus 12 performs a loop of sequentiallychanging the Y coordinate between steps S502 and S526 in the flowchart.In this loop, the image processing apparatus 12 increases the value of Yby 1 between 0 and a diffusion matrix height. For example, the diffusionmatrix height means the number of rows of the matrix used as thediffusion filter.

The image processing apparatus performs a loop of sequentially changingthe X coordinate between steps S504 and S524. In this loop, the imageprocessing apparatus 12 increases the value of X by 1 between 0 and adiffusion matrix width. For example, the diffusion matrix width meansthe number of columns of the matrix used as the diffusion filter.

In this loop, the image processing apparatus 12 first sets thecoordinate (X′, Y′) of the distribution destination, as shown in theflowchart. Then, the image processing apparatus sets a distributionratio depending on the diffusion filter (S506). At this time, the imageprocessing apparatus determines whether the distribution ratio is morethan 0 (S508), and performs the process of S504 again withoutdistributing the error when it is determined that the distribution ratiois equal to or less than 0 (No in S508).

When it is determined that the distribution ratio is more than 0 (Yes inS508), the image processing apparatus performs the process subsequent toS510. In this process, when the coordinate X′ of the distributiondestination is less than the image width (Yes in S510), the coordinateX′ is equal to or more than 0 (Yes in S512), and the coordinate Y′ ofthe distribution destination is less than the image height (Yes inS514), the image processing apparatus sets the error value (quantizationerror) to be distributed to the product of the error value and thedistribution ratio (S516) and adds the resultant to the distributionerror value stored in the accumulated error buffer (S518). Accordingly,the image processing apparatus 12 updates the accumulated error on thebasis of the generated quantization error.

When it is determined in S510 that the coordinate X′ is equal to or morethan the image width (No in S510), the image processing apparatus setsthe coordinate X′=X′−the image width and the coordinate Y′=Y′+1 (S520)and performs the process of S514. When it is determined in S512 that thecoordinate X′ is less than 0 (No in S512), the image processingapparatus sets the coordinate X′=X′+the image width and the coordinateY′=Y′+1 (S522) and performs the process of S514. When it is determinedin S514 that the coordinate Y′ is equal to or more than the image heightof the coordinate Y′ (No in S514), the image processing apparatus doesnot distribute the error but performs the process of S504.

By performing this operation, the image processing apparatus 12integrates the quantization error to the value stored in the accumulatederror buffer and calculates the accumulated error. According to thisexample, it is possible to appropriately distribute the error.Accordingly, it is possible to appropriately calculate the accumulatederror.

FIGS. 10( a)˜10(d) show examples of the printing result according tothis example along with the printing results according to referenceexamples. FIGS. 10( a) to 10(c) show the printing results according tothe reference examples different from this example described withreference to FIGS. 1 to 9. FIG. 10( a) shows an example of the printingresult when only a known typical error diffusion process is performed.FIG. 10( b) shows an example of the printing result when only a knowndither process is performed.

When only the typical error diffusion process is performed, the problemsuch as the dot delay is caused, for example, in the highlighted part orthe shadowed part. When only the dither process is performed, theproblem such as texture specific to the dither process is caused.

FIG. 10( c) shows an example of the printing result when the ditherprocess and the error diffusion process are simply switched depending onthe gray level range. In this example, between the highlighted part andthe halftone part or between the halftone part and the shadowed part,the switching process of slowly switching the noise use rate or theerror use rate as in this example is not performed but the ditherprocess and the error diffusion process are switched. In this way, whenthe dither process and the error diffusion process are simply switchedwithout performing an appropriate switching process, the problem such asthe generation of a boundary line is caused due to the switching.

FIG. 10( d) shows an example of the printing result according to thisexample. As can be seen from the drawing, according to this example, itis possible to appropriately suppress the dot delay in the highlightedpart or the shadowed part. It is also possible to appropriately preventthe generation of texture in the halftone part or the generation of aboundary line due to the switching. Accordingly, according to thisexample, it is possible to more appropriately perform the quantizationprocess.

While the invention has been described with reference to the embodiment,the technical scope of the invention is not limited to the range of theembodiment. It will be apparent to those skilled in the art that theembodiment maybe modified or improved in various forms. It can beclearly seen from the appended claims that the modifications orimprovements are included in the technical scope of the invention.

The quantization process is described above on the assumption that thenumber of gradations after the quantization is two. However, the samequantization process can be applied to, for example, a case where thenumber of gradations is three or more. The case where the number ofgradations is three or more means, for example, a case where three ormore types of dot sizes are used.

In this case, for example, the quantization processes corresponding tothe dot sizes are performed using both the dither matrix noise and theaccumulated error depending on the noise use rate and the error userate, identically or similarly to the case of two gradations. The outputresults corresponding to the dots of various sizes are compared and thedot of which the size is the largest is used as the final output.Accordingly, it is possible to more appropriately perform thequantization process, for example, even when the number of gradations isthree or more.

Industrial Applicability

The invention can be suitably used, for example, in a program causing acomputer to perform quantization.

Description of Reference Numerals and Signs

10: PRINTING SYSTEM

12: IMAGE PROCESSING APPARATUS

14: PRINTING MACHINE

The invention claimed is:
 1. A non-transitory computer-readable mediumstored with a program causing a computer to quantize a gray levelindicating the depth of color of each pixel in an image, thequantization comprising: a pixel selecting process of sequentiallyselecting pixels to be quantized; a use rate determining process ofdetermining a noise use rate indicating the degree to which a dithermatrix noise which is noise designated by a predetermined dither matrixhas an influence on the quantization and an error use rate indicatingthe degree to which an accumulated error obtained by accumulating aquantization error which is an error generated in the quantization onperipheral pixels has an influence on the quantization, in which thenoise use rate and the error use rate corresponding to the correspondingpixel are determined depending on the gray levels of the pixelssequentially selected through the pixel selecting process; and aquantization executing process of performing the quantization on thegray levels of the pixels sequentially selected through the pixelselecting process, in which the quantization is performed using thedither matrix noise based on the noise use rate corresponding to thecorresponding pixel and using the accumulated error based on the erroruse rate corresponding to the corresponding pixel.
 2. The non-transitorycomputer-readable medium according to claim 1, wherein the programcausing the computer to additionally perform on the pixels sequentiallyselected through the pixel selecting process: an error-corrected inputvalue calculating process of calculating an error-corrected input valuewhich is a gray level having been corrected on the basis of theaccumulated error, in which a value obtained by adding the product ofthe error use rate and the accumulated error corresponding to thecorresponding pixel to the gray level of the corresponding pixel iscalculated as the error-corrected input value; and a noise-correctedthreshold value calculating process of calculating a noise-correctedthreshold value which is a threshold value having been corrected on thebasis of the dither matrix noise as a threshold value used for thequantization, in which a value obtained by adding the product of thenoise use rate and the dither matrix noise corresponding to thecorresponding pixel to a predetermined initial threshold value iscalculated as the noise-corrected threshold value, wherein thequantization executing process performs the quantization by comparingthe noise-corrected threshold value and the error-corrected input valuewith each other.
 3. The non-transitory computer-readable mediumaccording to claim 1, wherein the quantization executing processincludes: a maximum value determining process of determining whether thegray level of the pixel which is the input value of the quantization isequal to the maximum value of an allowable gray level range; a minimumvalue determining process of determining whether the gray level of thepixel which is the input value is equal to the minimum value of theallowable gray level range; and a quantization value acquiring processof acquiring a quantization value as the result of the quantization,wherein when it is determined in the maximum value determining processthat the input value is equal to the maximum value, the quantizationvalue acquiring process acquires a value to be output when the graylevel is larger than the threshold value as the quantization value, andwherein when it is determined in the minimum value determining processthat the input value is equal to the minimum value, the quantizationvalue acquiring process acquires a value to be output when the graylevel is smaller than the threshold value as the quantization value. 4.The non-transitory computer-readable medium according to claim 1,wherein in determining the noise use rate and the error use rate, theuse rate determining process sets the noise use rate when the gray levelof the pixel is a gray level corresponding to one of a highlighted partand a shadowed part to a value larger than the noise use rate when thegray level of the pixel is a gray level corresponding to a halftone partof which the gray level is between the gray levels of the highlightedpart and the shadowed part, and sets the error use rate when the graylevel of the pixel is a gray level corresponding to one of thehighlighted part and the shadowed part to a value smaller than the erroruse rate when the gray level of the pixel is the gray levelcorresponding to the halftone part.
 5. The non-transitorycomputer-readable medium according to claim 4, wherein the use ratedetermining process sets the noise use rate to a value equal to orlarger than the lowest noise use rate set to a value larger than 0 inadvance even when the gray level of the pixel has any value.
 6. Thenon-transitory computer-readable medium according to claim 5, whereinthe use rate determining process uses a first highlight reference valueset in advance and a second highlight reference value larger than thefirst highlight reference value as a reference indicating the gray levelrange of the highlighted part; uses a first shadow reference value setin advance and a second shadow reference value larger than the firstshadow reference value as a reference indicating the gray level range ofthe shadowed part; uses a first halftone reference value which is largerthan the second highlight reference value and smaller than the firstshadow reference value and a second halftone reference value which islarger than the first halftone reference value and smaller than thefirst shadow reference value as a reference indicating the gray levelrange at the center of the halftone part; sets the noise use rate to 1when the gray level of the pixel is equal to or less than the firsthighlight reference value or when the gray level of the pixel is equalto or more than the second shadow reference value; sets the noise userate to the lowest noise use rate when the gray level of the pixel isequal to or more than the first halftone reference value and equal to orless than the second halftone reference value; sets the noise use rateto a value which is equal to or more than the lowest noise use rate andequal to or less than 1 and which gradually decreases from 1 dependingon the difference between the gray level of the pixel and the firsthighlight reference value when the gray level of the pixel is equal toor more than the first highlight reference value and equal to or lessthan the first halftone reference value; sets the noise use rate to avalue which is equal to or more than the lowest noise use rate and equalto or less than 1 and which gradually increases from the lowest noiseuse rate depending on the difference between the gray level of the pixeland the second halftone reference value when the gray level of the pixelis equal to or more than the second halftone reference value and equalto or less than the second shadow reference value; sets the error userate to 1 when the gray level of the pixel is equal to or more than thesecond highlight reference value and equal to or less than the firstshadow reference value; sets the error use rate to a value which isequal to or more than 0 and equal to or less than 1 and which graduallydecreases from 1 depending on the difference between the secondhighlight reference value and the gray level when the gray level of thepixel is equal to or less than the second highlight reference value; andsets the error use rate to a value which is equal to or more than 0 andequal to or less than 1 and which gradually decreases from 1 dependingon the difference between the gray level of the pixel and the firstshadow reference value when the gray level of the pixel is equal to ormore than the first shadow reference value.
 7. The non-transitorycomputer-readable medium according to claim 6, wherein the use ratedetermining process additionally uses a third highlight reference valuewhich is larger than 0 and equal to or less than the first highlightreference value as the reference indicating the gray level range of thehighlighted part; additionally uses a third shadow reference value whichis equal to or more than the second shadow reference value and smallerthan the maximum value of the allowable gray level range as thereference indicating the gray level range of the shadowed part; sets theerror use rate to 0 when the gray level of the pixel is equal to or lessthan the third highlight reference value; sets the error use rate to avalue obtained by dividing the difference between the gray level of thepixel and the third highlight reference value by the difference betweenthe second highlight reference value and the third highlight referencevalue when the gray level of the pixel is equal to or more than thethird highlight reference value and equal to or less than the secondhighlight reference value; sets the error use rate to a value obtainedby dividing the difference between the third shadow reference value andthe gray level of the pixel by the difference between the third shadowreference value and the first shadow reference value when the gray levelof the pixel is equal to or more than the first shadow reference valueand equal to or less than the third shadow reference value; and sets theerror use rate to 0 when the gray level of the pixel is equal to or morethan the third shadow reference value.
 8. An image processing apparatusquantizing a gray level indicating the depth of color of each pixel inan image, comprising: a pixel selecting unit that sequentially selectspixels to be quantized; a use rate determining unit that determines anoise use rate indicating the degree to which a dither matrix noisewhich is noise designated by a predetermined dither matrix has aninfluence on the quantization and an error use rate indicating thedegree to which an accumulated error obtained by accumulating aquantization error which is an error generated in the quantization onperipheral pixels has an influence on the quantization and thatdetermines the noise use rate and the error use rate corresponding tothe corresponding pixel depending on the gray levels of the pixelssequentially selected by the pixel selecting unit; and a quantizationexecuting unit that performs the quantization on the gray levels of thepixels sequentially selected by the pixel selecting unit and thatperforms the quantization using the dither matrix noise based on thenoise use rate corresponding to the corresponding pixel and using theaccumulated error based on the error use rate corresponding to thecorresponding pixel.
 9. An image processing method of quantizing a graylevel indicating the depth of color of each pixel in an image,comprising: a pixel selecting step of sequentially selecting pixels tobe quantized; a use rate determining step of determining a noise userate indicating the degree to which a dither matrix noise which is noisedesignated by a predetermined dither matrix has an influence on thequantization and an error use rate indicating the degree to which anaccumulated error obtained by accumulating a quantization error which isan error generated in the quantization on peripheral pixels has aninfluence on the quantization and determining the noise use rate and theerror use rate corresponding to the corresponding pixel depending on thegray levels of the pixels sequentially selected in the pixel selectingstep; and a quantization executing step of performing the quantizationon the gray levels of the pixels sequentially selected in the pixelselecting step and performing the quantization using the dither matrixnoise based on the noise use rate corresponding to the correspondingpixel and using the accumulated error based on the error use ratecorresponding to the corresponding pixel.